Phd Thesis In Knowledge Management

Program Description PhD Information and Knowledge Management The main research topics are information systems design methodologies, advanced techniques in information and knowledge processing. Organization The studies follow common Study and Examination Rules of the doctoral study programme. The study programme is outlined in such a way that students of each of the two mentioned fields of study attend the compulsory common basics consisting of four subjects: selected questions on the theory of economics general systems theory statistical and mathematical methods in management information and knowledge systems The student takes on at least two other subjects in addition to this common basic which are close to the chosen field of his or her studies.

Graduation Requirements credits or more The oral defense of the doctoral thesis Passing the state doctoral exams The duration of the programme: 4 years The tuition fee for one academic year: EUR. The deadline for submitting applications: 31st March. Read less. Hradec Kralove. View School Profile.

Program Dates When is the application deadline for this program? What is the start date for this program? Can I pay for this program in installments?

What is the duration of this program? In my opinion, KM is something new as it deals explicitly with knowledge one of the major problems in this discipline. KM-systems as such are also something new as they offer more KM oriented functions than traditional systems.

A more rigorous discussion of this topic can be found in a paper by Spiegler[98], which discusses the differences between some of the fields mentioned above and KM -systems.

This paper explains why KM is a new idea and not simply a recycled concept. This subject is also handled order homework the research carried out by Essers and Schreinemakers[34] in which they state, that simply establishing a strict referential distinction between knowledge and information will not automatically lead to a safe delineation between IM and KM.

After arguing the distinctions between KM and some close research fields, it is important to provide differentiations between KM and other management activities in general. A number of papers like that of Rollet[89] or Romhardt[88] centered on organizational development and denying that other approaches classify as KM deal with this important issue.

Other papers, e. Anklam[7], show that people use the label KM doctoral thesis on wind turbines activities not really contributing to the field the mentioned paper talks about technical communications and the changes since the beginning of the discipline. Since no generally accepted definition of knowledge exists, the same holds true for KM. Summing up, this section presents references to papers discussing the differences between KM and other fields in general as well as the boundaries of KM.

It, furthermore, demonstrates the importance of well-founded boundaries to activities just claiming to be KM a difficult task for a field lacking an exact definition. A similar definition is provided by Alavi and Leidner in a paper see[3] that also contains an overview of the possibilities of IT to support KM. Note, however, that while the term KM-system is often used for IT systems as in this thesis, other authors refer to doctoral thesis on knowledge management result of a KM initiative, including, for example, organizational and IT changes, when using the term KM-system.

This thesis, nevertheless, uses the narrow definition given in the last paragraph, and I hope that not too much confusion arises from this fact. Wong and Aspinwall[] recently published a paper discussing the relationship of KM and IT and come to the conclusion that they are not totally equivalent as KM consists of technological, technical, and social issues.

While this is true for many cases, especially those considered in this thesis, KM is possible without any help from IT, as it can consist solely of social and organizational changes. Since my thesis is centered on the relationship of KM and IT, the most important distinction is to be made between knowledge, that is already available as data and information, the additional amount of knowledge that can be made explicit, and other resources that may enable people to gain new knowledge and insights.

In the field of KM, the most commonly used classification of knowledge is that into tacit to make matters worse, sometimes called implicit and explicit knowledge. While explicit knowledge is a generally accepted term for phrased knowledge like a formula, tacit knowledge is not defined so clearly. Definitions can be found, for example, in Nonaka and Takeuchi[79] or, presenting a more theoretical point of view, in Dienes and Perner[27] containing a definition of the differences between implicit and explicit knowledge.

The term tacit knowledge was first mentioned by Michael Polanyi who wrote in in his book The Tacit Dimension p. Summing up, Polanyi views tacit doctoral thesis on internet dangers as a combination of bodily experience and practice.

Although explicitly citing Polanyi they use the term with a wider meaning by including cultural aspects like internalized judgments, norms, and ideals. While they do not rigorously define the term, one can find examples of what Nonaka views as tacit knowledge in his paper: A Dynamic Theory of Organizational Knowledge Creation[78]. The following paragraphs discuss the different meanings of the term tacit knowledge as used by Polanyi or Nonaka.


The arguments are based doctoral thesis on project management information obtained in discussions with my former colleague Dr. Johann Ortner. Nonaka says, These philosophical principles form the tacit knowledge base for Kao.

This tacit knowledge base guides doctoral thesis on corporate governance behavior of Kaos employees and serves as the key driver for its unique corporate culture. Thus, Nonaka discusses internalized norms that can be made explicit and ideals when mentioning the term tacit knowledge. Polanyi, on the other hand, is talking about the way higher life forms cats, dogs, birds, etc. More specifically, how entities like an apple are treated as a whole instead of just a number of frequencies of light registered in the eye.

The background of his research is based on empirical as well as Gestalt psychology. In his opinion, the knowledge to experience such entities as a whole is bodily knowledge, inaccessible to the linguistic and rational thought. Instead, it is the reference base for the meaning of certain words. Nonaka, on the other hand, views tacit knowledge as internalized necessities, challenges, and normative abstract dissertation international section that coerce people into being creative.

It is easy to see, consequently, that internalized knowledge about the environment that is shared with other higher life forms like cats and dogs is fundamentally different from internalized culture and, thus, there is a fundamental difference in the meaning of the term tacit knowledge as used by Nonaka compared to Polanyi.

This is not necessarily a problem but has to be taken into account when reading about tacit knowledge in KM literature, especially when both Polanyi and Nonaka are being cited as references.

While this model is better suited for my thesis, the used concept of tacit knowledge remains different from the original definition given by Polanyi. Thus, I conclude that it should be the focus of further doctoral thesis on english literature. Nevertheless, the popularity of the wider definition of tacit knowledge will make it necessary to sometimes use the terms implicit and tacit interchangeably. Consequently, there will be a remark or footnote in such a case.

Following the elaborate discussion of tacit, implicit, and explicit knowledge, I would like to present the embedded versus embodied differentiation in brief, to give one additional example of the numerous classifications of knowledge. It is easy to recognize that this model provides a different point of masters thesis citation and, thus, helps to gain a deeper understanding of the phenomenon knowledge.

Although this is very interesting for KM in general like the many other proposed differentiationsits importance for IT KM-systems is rather low. Therefore, I am not going to discuss this or any other classification in more detail. Up to now, this chapter focused on KM itself and on the possible role of IT in general. Therefore, a discussion what parts and processes of KM can be executed doctoral thesis on corporate governance supported by IT and in what areas this is not possible is still missing.

While this issue is often mentioned in KM literature, in-depth discussions like that of Johannessen et al. The two most important issues IT is incapable to manage are, on the one hand, cultural and organizational issues and, on the other hand, tacit knowledge. These topics are of utmost importance for any KM initiative and need to be addressed by non-IT means. Nevertheless, IT can provide some limited capabilities to support tacit knowledge transfer by allowing people to communicate, for example, with video conference capabilities.

Furthermore, existing IT systems will need to be adapted and newly introduced ones customized in accordance with necessary cultural and organizational changes. Consequently, it is possible to argue that IT is even supporting the cultural and organizational changes as well as tacit knowledge transfer. However, as IT systems are very limited with regard to these issues, they need to be addressed primarily outside the technological realm.

In the case of implicit knowledge, on the other hand, both IT and non-IT activities are necessary to ensure that all relevant pieces are made explicit and inserted into the KM-system. Finally, explicit knowledge, codified as information, is the domain of IT in the form of information management.

Although the management of information is done by the IT system, non-IT activities need to ensure that the system and its capabilities are embedded efficiently into the daily work processes. As a result, the available information is managed and made accessible in as many forms and ways as sensible, while at the same time being used as the data source for more advanced features that aim at generating new relevant information.

Such generated information is supposed to allow users to gain new insights, thus, ultimately generating new knowledge. Summing up, these last paragraphs demonstrate that IT and non-IT activities have to play their respective role in all three of the considered knowledge types. In the case of IT the focus is on managing information and providing communication possibilities.

On the other hand, non-IT activities have to take care of the cultural and organizational aspects and have to ensure that any IT support is aligned with the goals of the KM initiative and the organizational work procedures. Indeed, some of the presented technologies are - either alone or in combination - capable of supporting limited or specialized KM initiatives. Business software is widely used to support organizations in areas like human resources, finance, and resource planning, etc.

These systems represent a wide area of business related software products and are often called Enterprise Resource Planning ERP systems. Not only do they contain valuable data about employees, customers, organizational hierarchies, projects, etc. KM initiatives in organizations using business software most of the bigger ones do have two important tasks, namely to integrate the available information and, at least, the functions needed by the majority of the users the goal is to integrate as much functions as possible.

These systems contain highly relevant information and provide important functions. Thus, such systems should be integrated to enrich the KM-system if they are already in place. Groupware systems like Lotus Notes Domino or Microsoft Outlook Exchange are used for unstructured communication and collaboration. They provide functions for coordinating meetings, sharing documents, etc.

Often there are add-on products enabling even more doctoral thesis on talent management collaboration like multiple people working with one and the same document or extended communication facilities like chat or video conferencing. Furthermore, some of the functions provided by Groupware systems are of major importance for KM -systems and, thus, need to be integrated.

The primary objective of CRM is to provide customers with the best service possible by facilitating all available information about past contacts and purchases. At the same time, this information is used to find out what other products might be of interest to the individual customer ultimately generating increased sales.

Consequently, such systems can provide high quality information centered on customers, products, and feedback. Therefore, this information often will need to be incorporated in KM -systems.

Artificial Intelligence AI is a technology that most of the time is not directly visible to the user of KM or related systems.

This technology enables IT systems to appear smart by finding correlations, for example. Thus, it possibly is the single most important technology behind KM-systems, especially as it helps to differentiate KM-systems from IMS. Although AI is hidden most of the time from the user as it is difficult to handleexpert users sometimes need functions based on this technology to directly exploit and explore the available data and information in every possible way.

Although the technology behind all these areas is more or less the same, they try to achieve different goals. Detailed information on DM is, for example, available in papers by Petrak[85] or by Witten and Frank[]. For an introduction to ML, see Mitchell[76].

While the mentioned areas represent the most important ones, there are many other relevant technologies. Some are basic technologies like databases or middleware systems, while others are examples of more advanced ones.

Examples of the latter are geographical information systems or tools for devices with limited capabilities. Of course, there are numerous other technologies with a certain importance for KM-systems.

However, for introductory purposes this overview should suffice. Since this introduction is slowly reaching its end, it is time to define the focus and boundaries of this thesis.

It needs to be absolutely clear what is included and what is not. Generally speaking, I am proposing a KM-system and, therefore concentrating on technological issues of KM. Nevertheless, it is of utmost importance to consider KM as a whole for a sound foundation of such a system. From an organizational point of view, my solution should fit for many situations, although this thesis is concentrating on areas where flexibility, creativity, and learning are of high relevance.

Furthermore, mechanistic views of management are not considered, even though they often work reasonable well, as I am of the opinion, that the resulting behavior of management is not an appropriate foundation for my solution without being able to argue this in a rigorous fashion. The described system is intended for decision makers as well as individual staff containing all the features both groups need.

While it contains support for more conventional and standard requirements like document distribution, such requirements are more or less a side issue. The concept focuses on larger organizations that already have diverse systems in use and is more suited for non-routine tasks such as project management, software development, or more general product development.

Although such a system would also address similar issues financial accounting standards board by smaller organizations, it is probably too complex and expensive for their needs. Other researchers are trying to create tightly integrated IT systems that are based on conceptual knowledge. I think this approach is not feasible for the setting in question. While such a system should be superior from a technological point of view, a multitude of serious problems needs to be resolved first.

One of the most important issues is the lack of clearly defined company wide linguistic terms in larger organizations a problem sometimes also encountered in smaller ones. Consequently, I am not examining this topic in more detail. A definition of the distinction between high and low tangibility processes can be found in Grey[44].

As I am concentrating on the former one, this difference is of high importance for my thesis. Typical examples of high tangibility processes are project management, software development, or more general product development. While low tangibility KM processes, of course, also benefit from using the proposed solution, the net result is expected to be significantly lower.

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Low tangibility KM processes need far less support for flexibility and creativity and, therefore, are more concerned with automation workflowsprocesses To conclude this introduction, I would like to discuss relevant artifacts for KM -systems and possible classification systems for them.

For example, one is the distinction between structured and unstructured data. Another one is information itself e. It could just have easily been organizational behavior. Far too many students end up suffering from rabbit in headlight syndrome. Before you type a single word into your document you need to take some time out to make sure that you:. If you cannot do the above two things then you are going to seriously struggle to make anyone else understand you.

Cut to the chase and present it in a logical manner than leaves no room for ambiguity.

Enterprise Knowledge Management (EKM) › Schöller Endowed Chair for Information Systems

This is YOUR thesis.It is not easily replicated, reproduced or acquired, however, our history has shown that anything is possible with the right effort and this may be one skill that all humans possess.

Our greatness aside, talent management is a new concept that can prove to be quite valuable to mankind if addressed properly. Our history is dotted with prodigal individuals whose unique perception of reality revolutionized life for the rest of the human populations, examples are Einstein and Isaac newton. The goal of skills optimization is to establish set guidelines to optimize performance in organization to facilitate the accomplishment of strategic goals in a corporation.

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